A simulation model of the real-world fuel and energy consumption of light-duty vehicles
Nikiforos Zacharof, Stylianos Doulgeris, Alexandros Zafeiriadis, Athanasios Dimaratos, René van Gijlswijk, Sonsoles Díaz et al. · 2024 · 7 citationsRead the paper
The European Union has intensified efforts to reduce CO 2 emissions from the transport sector, with the target of reducing tailpipe CO 2 emissions from light-duty vehicle new registrations by 55% by 2030 and achieving zero emissions by 2035 according to the “Fit for 55” package. To promote fuel and energy consumption awareness among users under real-world conditions the MILE21—LIFE project provided tools such as a self-reporting tool and a find-a-car tool that included the official and representative on-road fuel/energy consumption values. In order to produce representative values, an in-house vehicle longitudinal dynamics simulation model was developed for use in the background of the on-line platform utilizing only a limited amount of inputs. To achieve this, the applied methodology is based on precalculated efficiency values. These values have been produced using vehicle micro-model simulations covering a wide range of operating conditions. The model was validated using measurements from a dedicated testing campaign and performed well for petrol vehicles with an average divergence of −1.1%. However, the model showed a divergence of 9.7% for diesel vehicles, 10.6% for hybrids and 8.7% for plug-in hybrids. The model was also applied to US vehicles and showed a divergence of 1.2% and 10% for city and highway driving, respectively. The application of the developed model presented in this work showed that it is possible to predict real-world fuel and energy consumption with the desired accuracy using a simplified approach with limited input data.
2 ideas Seedlabs derived from this research
A B2B software tool for automotive Tier-1 suppliers to provide OEMs with certified, real-world energy saving projections for lightweight parts. It replaces static industry averages with physics-based simulations and surrogate modeling to balance mass reduction with safety requirements.
AI score 86/100A B2B software tool for automotive engineers to quantify the fuel and energy savings of replacing heavy components with lightweight composites. The tool calculates ROI by balancing energy reduction against the material's lifecycle environmental and financial costs.
AI score 86/100